Nlogic-based methods for optimization pdf merger

A comprehensive survey of the literature on the cooperation of logic based, con. We propose a scheme based on two fundamental dualities. Optimization methods in 1122012 dsp 26 class algorithm function q q comp. Comparing time streams of economic benefits and costs. Lagrangian methods general formulation of constrained problems.

Inventory optimization in supply chain management using. A pioneering look at the fundamental role of logic in optimization and constraint satisfaction. Optimization of inventory strategies to enhance customer service, reduce lead times and costs and meet market demand 3, 15. The standard form of the general nonlinear, constrained optimization problem is presented, and various techniques for solving the resulting optimization problem are discussed.

There is nothing new about logicbased techniques for optimization. Future perspective on optimization ignacio grossmann. This approach can combine some of the problemsolving wisdom accumulated by mathematical programmers with techniques and insights from constraint pro. After the connection has been made such that the optimization software can talk to the engineering model, we specify the set of design variables and objectives and constraints. Optimization as well as constraint satisfaction methods can be seen as exploiting these dualities in their respective ways. Inventory optimization application aids in the enhancement of inventory control and its management across an extended supply network, which organizes the latest techniques and technologies. Yet no generally accepted principle or scheme for their merger has evolved. This paper proposes a logicbased approach to optimization that combines solution methods from mathematical programming and logic programming. Optimization, constraint programming, logicbased methods, artificial intelligence. Pdf logicbased methods for optimization researchgate.

We also indicate how semantic query optimization techniques can be extended to databases. Global optimization methods can generally be classified as stochastic and deterministic. Logicbased methods also provide a unified approach to solving optimization. The purpose of the following sections is to exhibit optimization algorithms that can be used for multiplequery optimization either as plan mergers or as global optimizers. Alternative plans, p, may involve different benefits and costs over time. Optimization methods are somewhat generic in nature in that many methods work for wide variety of problems.